Towards AoI-aware Smart IoT Systems

Age of Information (AoI) has gained importance as a Key Performance Indicator (KPI) for characterizing the freshness of information in information-update systems and time-critical applications. Recent theoretical research on the topic has generated significant understanding of how various algorithms perform in terms of this metric on various system models and networking scenarios. In this paper, by the help of the theoretical results, we analyzed the AoI behavior on real-life networks, using our two test-beds, addressing IoT networks and regular computers. Excessive number of AoI measurements are provided for variations of transport protocols such as TCP, UDP and web-socket, on wired and wireless links. Practical issues such as synchronization and selection of hardware along with transport protocol, and their effects on AoI are discussed. The results provide insight toward application and transport layer mechanisms for optimizing AoI in real-life networks

On the Role of Age of Information in the Internet of Things

In this article, we provide an accessible introduction to the emerging idea of Age of Information (AoI) that quantifies freshness of information and explore its possible role in the efficient design of freshness-aware Internet of Things (IoT). We start by summarizing the concept of AoI and its variants with emphasis on the differences between AoI and other well-known performance metrics in the literature, such as throughput and delay. Building on this, we explore freshness-aware IoT design for a network in which IoT devices sense potentially different physical processes and are supposed to frequently update the status of these processes at a destination node (such as a cellular base station). Inspired by the recent interest, we also assume that these IoT devices are powered by wireless energy transfer by the destination node. For this setting, we investigate the optimal sampling policy that jointly optimizes wireless energy transfer and scheduling of update packet transmissions from IoT devices with the goal of minimizing long-term weighted sum-AoI. Using this, we characterize the achievable AoI region. We also compare this AoI-optimal policy with the one that maximizes average throughput (throughput-optimal policy), and demonstrate the impact of system state on their structures. Several promising directions for future research are also presented.Comment: To appear in IEEE Communications Magazin

Age of Information in a Multisource Ber/Geo/1/1 Preemptive Queueing System

This work studies the information freshness of the vehicle-to-infrastructure status updating in Internet of vehicles, which is modeled as a multi-source Ber/Geo/1/1 preemptive queueing system with heterogeneous service time. We pay attention to both the distribution and average of AoI. To fully track the per-source AoI evolution, a Markov two-dimensional (2D) age process is introduced. The first element of the 2D age process stands for the instantaneous per-source AoI, while the second represents whether an update of the concerned source is being served and its current age. A complete framework and detailed analyses on the per-source AoI are presented based on the Markovity of the 2D age process. By studying the state transition probabilities, stationary equations, and stationary distribution of the 2D age process, analytical expressions of the probability mass function and average of per-source AoI are derived. Numerical results validate the accuracy of the theoretical analyses